EAGER: Collaborative Mathematics Learning with Robots

EAGER：与机器人协作数学学习

• 批准号: 1256780
• 负责人: Harry Cheng
• 金额: $ 30万
• 依托单位: University of California-Davis
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-01 至 2015-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1256780&HistoricalAwards=false
• 关键词: EAGER; Collaborative; Mathematics; Learning; Robots

This PI team asks (i) how to use the affordances of modular robotics for distributing work among individuals in a student groups to promote both better engagement and better learning among those learning algebra and (ii) what can be learned more generally from this effort about orchestrating and supporting learning when learners have available to them technology that supports distributed group work. One PI, a mechanical engineer, brings a novel modular robotics platform to this collaboration, one that has many affordances for supporting algebra learning, is quite engaging and has been found to draw in students who otherwise might not become excited about math learning, and that has affordances for supporting distributed cognition and hence suggests some new ways of promoting and supporting collaborative learning. The second PI, a learning scientist and mathematics education researcher, brings expertise in math learning and a nuanced understanding of the ways distributed cognition can be leveraged to promote collaborative math learning. It is possible that there are aspects of collaborative learning that are uniquely afforded by the robotics materials of the first PI and the kinds of project-solving challenges that can be built up around them. And there may be new kinds of collaborative behaviors that arise from use of such manipulatives that suggests new avenues for promoting learning. This EAGER project supports first steps in creating synergy between these two approaches and in making these intriguing ideas about promoting collaboration and math learning concrete. The technological innovation in this project is in learning how to use manipulatives with affordances for supporting distributed cognition to promote collaboration and how to effectively integrate use of such manipulates with use of software designed for collaborative math problem solving. The research is directed at shedding light on how to take advantage of manipulatives that can support distributed cognition and hence collaborative learning, and discovering some of the new kinds of collaborative behaviors that might arise from activities with such manipulatives and how to take advantage of those (or alleviate them) in promoting learning.The educational goals being addressed are both broader participation goals and learning goals, the idea being that "play" with engaging robots in the context of learning algebra and other disciplines will draw students in to the subject area at the same time it better promotes their learning. Algebra, in particular, is a gateway to more advanced STEM, and drawing more of the population into STEM careers requires drawing more of them into algebra learning and helping more of the population learn algebra well. The potential broader impacts are particularly strong with respect to gender and diversity. This project represents work in its early states on an untested but potentially transformative idea and is likely to catalyze rapid and innovative advances in the use of modular robotics and other computational manipulatives to broaden participation in STEM disciplines and promote deeper learning in those same disciplines.

这个PI团队询问（i）如何使用模块化机器人的启示在学生群体中的个人之间分配工作，以促进学习代数的人更好的参与和更好的学习，以及（ii）当学习者可以使用支持分布式小组工作的技术时，可以从这种关于编排和支持学习的努力中更普遍地学到什么。一位PI，一位机械工程师，为这次合作带来了一个新颖的模块化机器人平台，这个平台具有许多支持代数学习的启示，非常吸引人，并且已经发现吸引了那些否则可能不会对数学学习感到兴奋的学生，并且具有支持分布式认知的启示，因此提出了一些促进和支持协作学习的新方法。第二个PI是学习科学家和数学教育研究人员，他带来了数学学习方面的专业知识，以及对分布式认知如何被用来促进协作数学学习的细致入微的理解。有可能协作学习的某些方面是由第一个PI的机器人材料以及可以围绕它们建立的各种项目解决挑战所独特提供的。使用这种操纵手段可能会产生新的合作行为，这为促进学习提供了新的途径。这个EAGER项目支持在这两种方法之间建立协同作用的第一步，并使这些关于促进合作和数学学习的有趣想法具体化。该项目的技术创新是学习如何使用具有启示的操纵器来支持分布式认知以促进协作，以及如何有效地将此类操纵的使用与专为协作数学问题解决而设计的软件的使用集成起来。本研究旨在阐明如何利用能够支持分布式认知的操纵项，从而实现协作学习，并发现一些新的协作行为，这些行为可能会从使用此类操纵项的活动中产生，以及如何利用这些行为（或减轻它们）在促进学习方面的作用。正在处理的教育目标既是更广泛的参与目标，也是学习目标，这个想法是，在学习代数和其他学科的背景下与迷人的机器人“玩耍”，将吸引学生进入学科领域，同时更好地促进他们的学习。特别是代数，是通往更高级STEM的门户，吸引更多的人进入STEM职业需要吸引更多的人进入代数学习，并帮助更多的人学好代数。潜在的更广泛影响在性别和多样性方面尤其强烈。该项目代表了一个未经测试但可能具有变革性的想法的早期阶段的工作，并有可能促进模块化机器人和其他计算操作的快速和创新性进步，以扩大STEM学科的参与，并促进这些学科的深入学习。